Statistical experimental design was utilized to optimize removal of Methylene blue (MB) by Acer tree leaves through a batch biosorption process. Acer tree leaves were introduced as a novel and low cost biosorbent for removing MB from aqueous solutions. The influence of various factors, such as initial pH, initial concentration of dye and sorbent mass on the Methylene blue biosorption was investigated. A regression model was derived by using a response surface methodology (RSM) through performing the hybrid central composite design. The proposed quadratic model resulted from the hybrid design approach, which fitted very well to the experimental data. Model adequacy was checked through diagnostic tests, namely analysis of variance (ANOVA); a lack of fit test; and residuals distribution. The optimized condition for Methylene blue biosorption was calculated to be pH= 2.7; m= 0.05 g; and C= 928 mg/L. Furthermore, the isotherms and kinetics of biosorption were also explored.
